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vishalzambre

Honeybadger MCP Server

by vishalzambre

get_honeybadger_fault

Fetch a specific error from Honeybadger by ID to analyze and troubleshoot application issues directly in your development environment.

Instructions

Fetch a specific fault/error from Honeybadger by ID

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
fault_idYesThe ID of the fault to fetch
project_idNoOptional project ID (uses env var if not provided)

Implementation Reference

  • The handler function that executes the tool logic: fetches the fault details from Honeybadger API by ID and returns formatted JSON.
    private async getFault(faultId: string, projectId?: string): Promise<any> {
      const pid = projectId || this.config.projectId;
      if (!pid) {
        throw new McpError(ErrorCode.InvalidRequest, 'Project ID is required');
      }
    
      const data = await this.makeHoneybadgerRequest(`/projects/${pid}/faults/${faultId}`);
    
      return {
        content: [
          {
            type: 'text',
            text: JSON.stringify(data, null, 2),
          },
        ],
      };
    }
  • Input schema defining parameters for the get_honeybadger_fault tool: fault_id (required), project_id (optional).
    inputSchema: {
      type: 'object',
      properties: {
        fault_id: {
          type: 'string',
          description: 'The ID of the fault to fetch',
        },
        project_id: {
          type: 'string',
          description: 'Optional project ID (uses env var if not provided)',
        },
      },
      required: ['fault_id'],
    },
  • src/index.ts:94-111 (registration)
    Registration of the get_honeybadger_fault tool in the listTools response, including name, description, and schema.
    {
      name: 'get_honeybadger_fault',
      description: 'Fetch a specific fault/error from Honeybadger by ID',
      inputSchema: {
        type: 'object',
        properties: {
          fault_id: {
            type: 'string',
            description: 'The ID of the fault to fetch',
          },
          project_id: {
            type: 'string',
            description: 'Optional project ID (uses env var if not provided)',
          },
        },
        required: ['fault_id'],
      },
    },
  • Switch case in the central CallToolRequest handler that dispatches to the getFault method.
    case 'get_honeybadger_fault':
      return await this.getFault(args.fault_id as string, args.project_id as string | undefined);
  • Helper method used by getFault to make authenticated API requests to Honeybadger.
    private async makeHoneybadgerRequest(endpoint: string, params: any = {}) {
      if (!this.config.apiKey) {
        throw new McpError(ErrorCode.InvalidRequest, 'HONEYBADGER_API_KEY environment variable is required');
      }
    
      const username = this.config.apiKey;
      const password = '';
      const url = `${this.config.baseUrl}/v2${endpoint}`;
      const credentials = Buffer.from(`${username}:${password}`).toString('base64');
    
    
      try {
        const response = await axios.get(url, {
          headers: {
            'Authorization': `Basic ${credentials}`,
            'Accept': 'application/json',
          },
          params,
        });
    
        return response.data;
      } catch (error: any) {
        if (error.response) {
          throw new McpError(
            ErrorCode.InvalidRequest,
            `Honeybadger API error: ${error.response.status} - ${error.response.data?.error || error.response.statusText}`
          );
        }
        throw new McpError(ErrorCode.InternalError, `Network error: ${error.message}`);
      }
    }
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the action ('Fetch') but does not describe what 'fetch' entails—e.g., whether it's a read-only operation, requires authentication, has rate limits, or what the return format looks like. For a tool with zero annotation coverage, this leaves significant gaps in understanding its behavior.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, efficient sentence that front-loads the core purpose ('Fetch a specific fault/error from Honeybadger by ID'). There is no wasted language or redundancy, making it highly concise and well-structured for quick understanding.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the lack of annotations and output schema, the description is incomplete. It does not cover behavioral aspects like safety, authentication, or response format, which are crucial for a tool that fetches data. While the purpose is clear, the overall context for effective use by an AI agent is insufficient.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, with both parameters ('fault_id' and 'project_id') fully described in the schema. The description adds no additional meaning beyond what the schema provides, such as explaining parameter interactions or usage nuances. Baseline 3 is appropriate when the schema does the heavy lifting.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the specific action ('Fetch') and resource ('a specific fault/error from Honeybadger by ID'), distinguishing it from sibling tools like 'list_honeybadger_faults' (which presumably lists multiple faults) and 'get_honeybadger_notices' (which fetches notices rather than faults). It precisely communicates the tool's function without ambiguity.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage by specifying 'by ID,' suggesting it's for retrieving a single, known fault. However, it does not explicitly state when to use this tool versus alternatives like 'list_honeybadger_faults' or 'analyze_honeybadger_issue,' nor does it mention prerequisites or exclusions. The guidance is implied but lacks explicit comparison.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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